1. Field of the Invention
The present invention generally relates to a method of motion detection, and more particularly, to a method of motion detection using an adaptive threshold.
2. Description of Related Art
With development of multimedia technique, requirement for image quality is substantially increased. The image quality may be influenced by the noises generated during image capturing, signal conversion and signal transmission. Therefore, an image processing technique is required to eliminate the noises that may be sensed by human eyes. The image processing methods for noise reduction commonly include a spatial noise-reduction process and a temporal noise-reduction process.
The spatial noise-reduction process applies a filter to perform spatial filtering process on the pixels of a current field, so as to smooth and soften the field, and reduce a visual perception of the human eyes for the noises. However, such method generally leads to image blurs, which may influence the presentation of image details, such as edges and textures, for example.
The temporal noise-reduction process references information of a previous field, so as to perform temporal filtering process to the pixels of the current field. Since the current field is highly related to the previous field, the temporal noise-reduction process can maintain and reserve details of the field. However, when the temporal filtering process is performed on a moving object within the field, motion blurs may occur on the edges of the moving object. Therefore, a motion detection algorithm is provided to detect the moving pixels in the field, so as to adjust an intensity of the temporal filtering for eliminating the motion blurs.
Generally speaking, motion detection uses differnces between correpsonding pixels in the same parity field to determine whether the designated pixels are moving pixels or not. If the difference is larger than a preset threshold, it means a variation is occurred in the content of the video and the corresponding pixels are determined as the moving pixels. On the other hand, if the difference is smaller than the preset threshold, it means no variation is occurred in the content of the video and the corresponding pixels are determined as the static pixels.
Through the motion detection as described above, motion information of pixels of the moving object is obtained and referenced for determining whether to use a spatial interpolation or a temporal interpolation method to generate the required field data, in which the temperal interpolation is used for calculating values of pixels in an area with no moving object and the spacial interpolation is used for calculating values of pixels in an area with the moving object.
As described in the above, the motion detection algorithm is complicated and requires a large amount of calculation. The value of the threshold used for determining a moving area and a static area is hard to formulate, in which the moving area can be mistakenly determined as the static area by using excessively large threshold while the static area can be mistakenly determined as the moving area by using excessively small threshold. Therefore, there is a need to well define a threshold as a reference for judging the moving area and the static area, so as to increase the accuracy of motion detection.